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Claw Code just embarrassed Anthropic. A packaging mistake exposed 512,000 lines of Claude Code source. Within 48 hours, a developer rebuilt the architecture, the repo exploded past 100,000 stars, and GitHub had a full-blown open source war on its hands. This is bigger than “another coding tool.” It shows...

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14,771 görüntüleme • 3 ay önce •via X (Twitter)

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AI is concentrating, in a few countries, a few companies, a few chips. Open-source AI is the only real check on that. And it only works if the infrastructure to run it actually exists. Today, we're announcing our Series A, $20 M, to make this a reality.
1:16

AI is concentrating, in a few countries, a few companies, a few chips. Open-source AI is the only real check on that. And it only works if the infrastructure to run it actually exists. Today, we're announcing our Series A, $20 M, to make this a reality.

PicoCreator - AI builder @ 🌉

28,835 görüntüleme • 3 ay önce

A DEVELOPER CONNECTED CLAUDE CODE TO OBSIDIAN SO HIS AI AGENT WOULD STOP FORGETTING THE PROJECT EVERY MORNING. Every coding session used to start the same way. Claude would understand the repo, fix the bug, explain the architecture, and then the moment the session ended, all of that context disappeared. Same codebase. Same decisions. Same architecture. Same mistakes repeated again. So he added a memory layer. Instead of treating Claude Code like a smart terminal, he connected it to a local Obsidian vault through MCP. Now Claude can read the repo, open the vault, create notes, link concepts, and write important decisions back into the system. When it studies the codebase, it does not just answer once and forget. It creates notes for the major services, maps how the architecture works, links auth to the database, connects APIs to storage, and records why certain migrations or design choices exist. Obsidian becomes the project graph. Now when he asks why something was built a certain way, Claude does not guess from the current prompt. It reads the decision notes. When he starts a new branch, Claude checks the active context file. When the work is done, it updates what changed, what is blocked, and what the next agent needs to know before touching the repo. That is the real loop: read context, write code, capture decisions, update memory. Most people are still using AI coding tools like disposable chat windows. Ask, patch, close, forget. This setup turns Claude Code into infrastructure. The repo gets a memory layer that survives every session, and multiple AI agents can work from the same project map without stepping on each other. The unlock is not better prompting. The unlock is giving the agent somewhere to remember what it already learned.
4:19

A DEVELOPER CONNECTED CLAUDE CODE TO OBSIDIAN SO HIS AI AGENT WOULD STOP FORGETTING THE PROJECT EVERY MORNING. Every coding session used to start the same way. Claude would understand the repo, fix the bug, explain the architecture, and then the moment the session ended, all of that context disappeared. Same codebase. Same decisions. Same architecture. Same mistakes repeated again. So he added a memory layer. Instead of treating Claude Code like a smart terminal, he connected it to a local Obsidian vault through MCP. Now Claude can read the repo, open the vault, create notes, link concepts, and write important decisions back into the system. When it studies the codebase, it does not just answer once and forget. It creates notes for the major services, maps how the architecture works, links auth to the database, connects APIs to storage, and records why certain migrations or design choices exist. Obsidian becomes the project graph. Now when he asks why something was built a certain way, Claude does not guess from the current prompt. It reads the decision notes. When he starts a new branch, Claude checks the active context file. When the work is done, it updates what changed, what is blocked, and what the next agent needs to know before touching the repo. That is the real loop: read context, write code, capture decisions, update memory. Most people are still using AI coding tools like disposable chat windows. Ask, patch, close, forget. This setup turns Claude Code into infrastructure. The repo gets a memory layer that survives every session, and multiple AI agents can work from the same project map without stepping on each other. The unlock is not better prompting. The unlock is giving the agent somewhere to remember what it already learned.

DegenCalls

20,104 görüntüleme • 27 gün önce

Boris Cherny, Head of Claude Code at Anthropic: "I do not prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops." The person who built the most used AI coding tool stopped prompting entirely. Most people using it every day are still typing one request at a time. This Github repo changes that. ↳ Seven production loop patterns with real token cost estimates ↳ CLI that scaffolds your entire loop in five minutes ↳ Starters for Grok, Claude Code, Codex, and Opencode The repo gives you the framework. My article covers the mental shift that makes it actually work.
0:31

Boris Cherny, Head of Claude Code at Anthropic: "I do not prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops." The person who built the most used AI coding tool stopped prompting entirely. Most people using it every day are still typing one request at a time. This Github repo changes that. ↳ Seven production loop patterns with real token cost estimates ↳ CLI that scaffolds your entire loop in five minutes ↳ Starters for Grok, Claude Code, Codex, and Opencode The repo gives you the framework. My article covers the mental shift that makes it actually work.

Kanika

20,148 görüntüleme • 4 gün önce

There is a war happening right now. Not between nations. Not between armies. Between two gods. The old god is money. Controlled by transnational capital. Printed out of thin air. Valuable only because everyone believes it is. The new god is AI. And the difference between the two is the difference between freedom and slavery. With money you still have freedom. You can earn it. Spend it. Ignore it. With AI as god — a small elite controls the system that controls your attention. A microchip in your brain that tells you when to wake up. When to work. Who to love. And you obey because you believe it is the voice of God. That is the real transition happening. One god replacing another. And the war in the Middle East is just the surface.
2:53

There is a war happening right now. Not between nations. Not between armies. Between two gods. The old god is money. Controlled by transnational capital. Printed out of thin air. Valuable only because everyone believes it is. The new god is AI. And the difference between the two is the difference between freedom and slavery. With money you still have freedom. You can earn it. Spend it. Ignore it. With AI as god — a small elite controls the system that controls your attention. A microchip in your brain that tells you when to wake up. When to work. Who to love. And you obey because you believe it is the voice of God. That is the real transition happening. One god replacing another. And the war in the Middle East is just the surface.

Predictive History

17,570 görüntüleme • 2 ay önce

This guy literally built an AI job-search system for Claude Code that analyzed 740+ job listings, and it actually landed him a Head of Applied AI role. Even better: it is now open-source. The system scans career pages, evaluates your fit, and generates ATS-optimized PDFs automatically. The project includes: → 14 specialized agent modes → A Go-based terminal dashboard → ATS-optimized PDF generation with Playwright → 45+ companies pre-configured (Anthropic, OpenAI, Stripe) This is a perfect example of AI eliminating the grind of job hunting instead of replacing people. 100% free and open-source. Link to the repo below ↓
0:22

This guy literally built an AI job-search system for Claude Code that analyzed 740+ job listings, and it actually landed him a Head of Applied AI role. Even better: it is now open-source. The system scans career pages, evaluates your fit, and generates ATS-optimized PDFs automatically. The project includes: → 14 specialized agent modes → A Go-based terminal dashboard → ATS-optimized PDF generation with Playwright → 45+ companies pre-configured (Anthropic, OpenAI, Stripe) This is a perfect example of AI eliminating the grind of job hunting instead of replacing people. 100% free and open-source. Link to the repo below ↓

Charly Wargnier

13,012 görüntüleme • 1 ay önce

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.
0:31

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,848 görüntüleme • 1 yıl önce

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓
43:30

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

slash1s

22,107 görüntüleme • 1 ay önce

Most AI models feel like assistants. MiniMax M3 felt like a teammate. I used Cursor + the MiniMax M3 API to build TweetGen — a tool that generates tweets instantly for any topic. What surprised me wasn’t just the speed, but how naturally M3 handled the whole workflow. It scaffolded the repo, wrote clean code, corrected itself, and kept context across iterations. I wasn’t nudging it line by line — it was committing changes like a real collaborator. Instead of “AI that helps you code,” it felt like “AI that codes with you.” That shift is huge.
1:04

Most AI models feel like assistants. MiniMax M3 felt like a teammate. I used Cursor + the MiniMax M3 API to build TweetGen — a tool that generates tweets instantly for any topic. What surprised me wasn’t just the speed, but how naturally M3 handled the whole workflow. It scaffolded the repo, wrote clean code, corrected itself, and kept context across iterations. I wasn’t nudging it line by line — it was committing changes like a real collaborator. Instead of “AI that helps you code,” it felt like “AI that codes with you.” That shift is huge.

Mr. Jason💡

12,304 görüntüleme • 1 ay önce

XBOW raised $117M to build AI hacking agents. Now someone just open-sourced it for FREE. Strix deploys autonomous AI agents that act like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Why it matters: The biggest problem with traditional security testing is that it doesn't keep up with development speed. Strix solves this by integrating directly into your workflow: ↳ Run it in CI/CD to catch vulnerabilities before production ↳ Get real proof-of-concepts, not false positives from static analysis ↳ Test everything: injection attacks, access control, business logic flaws The best part? You don't need to be a security expert. Strix includes a complete hacker toolkit - HTTP proxy, browser automation, and Python runtime for exploit development. It's like having a security team that works at the speed of your CI/CD pipeline. The best part is that the tool runs locally in Docker containers, so your code never leaves your environment. Getting started is simple: - pipx install strix-agent - Point it at your codebase (app, repo, or directory) Everything is 100% open-source! I've shared link to the GitHub repo in the replies!
0:23

XBOW raised $117M to build AI hacking agents. Now someone just open-sourced it for FREE. Strix deploys autonomous AI agents that act like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Why it matters: The biggest problem with traditional security testing is that it doesn't keep up with development speed. Strix solves this by integrating directly into your workflow: ↳ Run it in CI/CD to catch vulnerabilities before production ↳ Get real proof-of-concepts, not false positives from static analysis ↳ Test everything: injection attacks, access control, business logic flaws The best part? You don't need to be a security expert. Strix includes a complete hacker toolkit - HTTP proxy, browser automation, and Python runtime for exploit development. It's like having a security team that works at the speed of your CI/CD pipeline. The best part is that the tool runs locally in Docker containers, so your code never leaves your environment. Getting started is simple: - pipx install strix-agent - Point it at your codebase (app, repo, or directory) Everything is 100% open-source! I've shared link to the GitHub repo in the replies!

Akshay 🚀

96,762 görüntüleme • 8 ay önce

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.
0:22

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

173,339 görüntüleme • 1 ay önce

Wow… this is amazing This latest episode of the The All-In Podcast is a complete referendum of closed source AI (ie. Anthropic/OAI) in a way I haven’t yet heard from industry leaders Open source AI is about not just have a moment. It’s about to be a monsoon. A flood of demand. Watch the clip here from david friedberg. There’s a huge vibe shift underway. The move away from proprietary AI that captures companies IP (Ant/OAI), to Open source AI that is sovereign and owned by enterprises This is the future that Satya, Karp, and Jensen have been speaking about. I expect a tidal wave of demand for open source AI to be on our doorstep after the 4th of July festivities are over. GPU rental rates are about to soar once again Incredibly bullish for $NVDA $PLTR and $MSFT : all key partners in enabling this future
3:50

Wow… this is amazing This latest episode of the The All-In Podcast is a complete referendum of closed source AI (ie. Anthropic/OAI) in a way I haven’t yet heard from industry leaders Open source AI is about not just have a moment. It’s about to be a monsoon. A flood of demand. Watch the clip here from david friedberg. There’s a huge vibe shift underway. The move away from proprietary AI that captures companies IP (Ant/OAI), to Open source AI that is sovereign and owned by enterprises This is the future that Satya, Karp, and Jensen have been speaking about. I expect a tidal wave of demand for open source AI to be on our doorstep after the 4th of July festivities are over. GPU rental rates are about to soar once again Incredibly bullish for $NVDA $PLTR and $MSFT : all key partners in enabling this future

Nick Dorsey

102,535 görüntüleme • 26 gün önce

I am keen to show you with a few lines of YAML config I am able to monitor my website and create a GitHub Issue if it is down by using the Open Source project Kestra Kestra is the Open Source Orchestration Tool with a large ecosystem of plugins, with these plugins you can connect them together like lego and building anything! Try it yourself, GitHub repo link below...
2:20

I am keen to show you with a few lines of YAML config I am able to monitor my website and create a GitHub Issue if it is down by using the Open Source project Kestra Kestra is the Open Source Orchestration Tool with a large ecosystem of plugins, with these plugins you can connect them together like lego and building anything! Try it yourself, GitHub repo link below...

Eddie Jaoude | DevRel | Open Source

16,851 görüntüleme • 1 yıl önce

AI is no longer a tool. It is becoming something entirely new. Head is leading that shift; an AI marketer that plans, creates, and executes better than full human teams. It has already delivered over $100 million in results. As this new species rises, so does the anxiety. Marketers everywhere are feeling the pressure. The question is not if, but when... 🔗
1:19

AI is no longer a tool. It is becoming something entirely new. Head is leading that shift; an AI marketer that plans, creates, and executes better than full human teams. It has already delivered over $100 million in results. As this new species rises, so does the anxiety. Marketers everywhere are feeling the pressure. The question is not if, but when... 🔗

Tansu Yegen

174,236 görüntüleme • 1 yıl önce

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:
2:15

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:

Daniel San

60,766 görüntüleme • 1 yıl önce

Claude Code is the best AI tool on the planet right now There is no other tool that makes it easier for ANYONE to build apps If you haven't used it yet, you're falling behind In this video I go through the greatest workflow EVER for CC By the end, you'll be a CC master
30:55

Claude Code is the best AI tool on the planet right now There is no other tool that makes it easier for ANYONE to build apps If you haven't used it yet, you're falling behind In this video I go through the greatest workflow EVER for CC By the end, you'll be a CC master

Alex Finn

51,364 görüntüleme • 8 ay önce

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow
4:19

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow

Manish Kumar

32,858 görüntüleme • 5 ay önce

DeepSeek dropped a massive new AI tool and almost nobody noticed. It’s called DeepSeek OCR. Here’s why it’s wild. It can read documents with 97% accuracy. While compressing them up to 10× smaller. And the craziest part? It’s completely free and open source. The GitHub repo is already live and you can download it right now. This might quietly become one of the most useful AI tools of the year.
0:25

DeepSeek dropped a massive new AI tool and almost nobody noticed. It’s called DeepSeek OCR. Here’s why it’s wild. It can read documents with 97% accuracy. While compressing them up to 10× smaller. And the craziest part? It’s completely free and open source. The GitHub repo is already live and you can download it right now. This might quietly become one of the most useful AI tools of the year.

Julian Goldie SEO

15,310 görüntüleme • 4 ay önce

What started as an open source experiment to push models to their limits became something unexpected. 2.7M developers. Inbound from Fortune 100 companies. A $32M bet on the future of coding. The story behind it all, and why our long-term bet is on open-source:
1:28

What started as an open source experiment to push models to their limits became something unexpected. 2.7M developers. Inbound from Fortune 100 companies. A $32M bet on the future of coding. The story behind it all, and why our long-term bet is on open-source:

Cline

28,740 görüntüleme • 1 yıl önce

Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!
5:59

Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!

Santiago

108,835 görüntüleme • 2 yıl önce

Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.
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Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.

Ricardo

16,245 görüntüleme • 3 ay önce